Methods: CHC patients in Washington State and DC (N=159) completed a 47-item, self-administered questionnaire. The instrument assessed: (1) Practice Factors: use of smartphone to access wellness information, frequency of using smartphones for wellness, and use of health-based mobile apps. Multiple regression analyses assessed the impact of socio-demographic predictors (age, gender, race, employment, and income) on practice factors.
Results: Mean age was 35.98 years; mostly women (68%); White (36%); income below $20k/year (63%); and, high-school educated (53%). Smartphone Use for Wellness: 76% of respondents reported ever using smartphones for wellness with 33% doing so weekly. Age and employment status were statistically significant predictors of using smartphones for wellness; adults 50 years of age and older were significantly less likely to use their smartphones for wellness compared to adults 30 – 49 years of age (OR: 0.94; 95% CI: 0.88, 0.99), and ‘retirees/homemakers/individuals not looking for work’ were significantly less likely to report using smartphones for wellness compared to individuals working part/full-time (OR: 0.17; 95% CI: 0.03 – 0.83). Use of Health Apps: 48% of patients reported ever using health apps. Two most common health apps owned were calorie tracking (38%) and step monitoring (28%). Age and income were statistically significant predictors of health app use; adults 50 years of age and over were significantly less likely than adults 30 – 49 years of age to use health apps (OR: 0.95; 95% CI: 0.91 – 0.99), and respondents earning less than $20k/year were less likely to use health apps compared to individuals earning more, (OR: 3.13; 95% CI: 1.02 – 9.57).
Conclusion: Our study findings suggest that low-income patients are using mobile health technologies. Technologists must target older adults in app development as they are less likely to use mobile health devices but are affected by multiple chronic health conditions.